Optimized and kinematically feasible multi-agent motion planning

• URL: http://arxiv.org/abs/2605.01996v1
• Date: Sun, 03 May 2026 17:54:56 GMT
• Title: Optimized and kinematically feasible multi-agent motion planning
• Abstract summary: Multi-agent motion planning (MAMP) is an important problem for autonomous systems with multiple agents.<n>We propose a two-step method for finding optimized and kinematically feasible solutions to MAMP problems.<n>We evaluate our proposed framework on a MAMP problem for tractor-trailer systems.
• Score: 0.6299766708197881
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Multi-agent motion planning (MAMP) is an important problem for autonomous systems with multiple agents. In this work we propose a two-step method for finding optimized and kinematically feasible solutions to MAMP problems. The first step finds an initial feasible solution using state-of-the-art methods such as conflict-based search (CBS) or priority-based search (PBS), and the second step is an improvement step which improves the solution by solving a multi-phase optimal control problem (OCP) where the initial solution is used to warm-start the solver. We also propose a method for generating motion primitives in an optimized way under the constraint that the primitive durations are all multiples of the same sample time. We evaluate our proposed framework on a MAMP problem for tractor-trailer systems. We extend the safe interval path planning with interval projections (SIPP-IP) algorithm so it can handle more general cost functions and larger agents, but our results show that for the tractor-trailer system a simple lattice-based planner performs better due to less conservative collision checks. Our experiments also indicate that CBS performs better than PBS for this system as it achieves a higher success rate in environments with obstacles and had a lower average runtime, although both planners achieve solutions of similar quality after the improvement step.

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